ISSN 0253-2778

CN 34-1054/N

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Research on cognition-based hierarchical model for the construction and analysis of scenarios in chance discovery

  • 1.

    School of Management, Anhui Jianzhu University, Hefei 230022, China

  • 2.

    Anhui provincial Key Laboratory of Intelligent Building, Anhui Jianzhu University, Hefei 230022, China

Cite this:
https://doi.org/10.3969/j.issn.0253-2778.2016.01.010
  • Received Date: 27 August 2015
  • Accepted Date: 29 September 2015
  • Rev Recd Date: 29 September 2015
  • Publish Date: 30 January 2016
    Abstract

  • Abstract

    To identify and manage chance events effectively, a cognition-based hierarchical model for the construction and analysis of scenarios in chance discovery is presented according to cognitive information processing theory with the cognitive situation model, the process characteristic of cognition and the information filter mechanism of attention in cognition as references. The new model is composed of five information processes from bottom to top such as acquisition of private views, construction of private scenarios, integration of scenarios, generalization of scenarios and scenario analysis. Problems such as the acquisition of event clusters based on cognition, the representation and evolution of attention oriented to the implementation of filter mechanisms of attention, the construction of event clusters in chance diacovery scenarios, the aggregation of chance discovery scenarios, the implementation of the association phenomenon in the construction and analysis of chance discovery scenarios are discussed in detail. If cluster partition is treated as the chance discovery scenario and the chance discovery scenario is constructed as the aggregation of some private chance discovery scenarios where one private chance discovery scenario is one kind of cluster partition on dataset. Exmperimental results show that the accuracy of the cluster partition can be improved significantly.

    Abstract

    To identify and manage chance events effectively, a cognition-based hierarchical model for the construction and analysis of scenarios in chance discovery is presented according to cognitive information processing theory with the cognitive situation model, the process characteristic of cognition and the information filter mechanism of attention in cognition as references. The new model is composed of five information processes from bottom to top such as acquisition of private views, construction of private scenarios, integration of scenarios, generalization of scenarios and scenario analysis. Problems such as the acquisition of event clusters based on cognition, the representation and evolution of attention oriented to the implementation of filter mechanisms of attention, the construction of event clusters in chance diacovery scenarios, the aggregation of chance discovery scenarios, the implementation of the association phenomenon in the construction and analysis of chance discovery scenarios are discussed in detail. If cluster partition is treated as the chance discovery scenario and the chance discovery scenario is constructed as the aggregation of some private chance discovery scenarios where one private chance discovery scenario is one kind of cluster partition on dataset. Exmperimental results show that the accuracy of the cluster partition can be improved significantly.
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    • References(31)
  • [1]
    Ohsawa Y. Chance Discovery[M]. Springer- Verlag, 2003.
    [2]
    Abe A. Cognitive chance discovery: From abduction to affordance and curation[J] International Journal of Cognitive Informatics and Cognitive Computing, 2013, 8(2): 308-314.
    [3]
    McBurney P, Parsons S. Chance discovery and scenario analysis[J]. New Generation Computing, 2003, 21(1): 13-22.
    [4]
    张振亚, 程红梅, 王煦法. 从数据挖掘到机会/征兆发现[J]. 计算机科学, 2007, 34(10): 188-191.
    [5]
    张振亚, 程红梅, 张曙光. 基于六度分离理论的机会发现场景构造方法[J]. 模式识别与人工智能, 2011, 24(3): 332-339.
    Zhang Z Y, Cheng H M, Zhang S G. Anapproach to construction of scenario map in chance discovery based on six degree of separation theory[J]. Pattern Recognition and Artificial Intelligence, 2011, 24(3): 332-339.
    [6]
    张振亚, 程红梅, 张曙光. 机会发现中简单场景构造方法研究[J]. 计算机工程, 2011, 37(8): 192-193, 196.
    Zhang Z Y, Cheng H M, Zhang S G.Research on approach of simple scenario map construction in chance discovery[J]. Computer Engineering, 2011, 37(8): 192-193, 196.
    [7]
    Rybakov V V. Chance discovery and unification in linear modal logic[C]// Proceeding of 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Kaiserslautern, Germany: Springer, 2011: 478-485.
    [8]
    Chiu T F. An integration of grounded theory and chance discovery to explore the technology opportunity[J]. International Journal of Intelligent Information and Database Systems, 2012, 6(3): 231-254.
    [9]
    Abe A. Relation between chance discovery and Black Swan awareness[C]// Proceeding of 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Kaiserslautern, Germany: Springer, 2011: 495-504.
    [10]
    Ohsawa Y, Matsumura N, Okazaki N. Understanding scenarios of individual patients of hepatitis in double helical process involving KeyGraph and DSV[C]// Proceeding of 4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology. Springer, 2005:456-469.
    [11]
    Ohsawa Y, Nara Y. Understanding Internet users on double helical model of chance-discovery process[C]// Proceedings of the IEEE International Symposium on Intelligent Control. Baltimore, USA: IEEE Press, 2002: 844-849.
    [12]
    Oehlmann R, Gill B. A diagrammatic approach to discovering chances in team relationships[C]// Proceedings of 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Kaiserslautern, Germany: Springer, 2011:440-441
    [13]
    何先友，杨惠，李惠娟，等. 空间情境模型的更新：认知方式的影响[J]. 心理学报，2011，43(11): 1247-1262.
    [14]
    李金波，许百华，田学红.人机交互中认知负荷变化预测模型的构建[J]. 心理学报，2010，42(5): 559-568.
    [15]
    王沛，林崇德. 社会认知的理论模型综述[J].心理科学，2002，25(1): 73-75.
    [16]
    Gasson S, Waters J. Using a grounded theory approach to study online collaboration behaviors[J]. European Journal of Information Systems, 2013, 22(1): 95-118.
    [17]
    Hoda R, Noble J, Marshall S. Developing a grounded theory to explain the practices of self-organizing Agile teams[J]. Empirical Software Engineering, 2012, 17(6): 609-639.
    [18]
    Chien Ming-Kuei, Chang Te-Ming, Kuo Wei-Chun, Applying Grounded Theory to study green supply chain management practices in Taiwan's industry[C]// International Technology Management Conference. Bangalore, India: IEEE Press, 2012: 129-136.
    [19]
    Chiu T F. An integration of grounded theory and chance discovery to explore the technology opportunity[J]. International Journal of Intelligent Information and Database Systems, 2012, 6(3): 231-254.
    [20]
    Yang F S, Wang A L, Yang Y T. Using chance discovery in recruiting strategies to explore potential students in Taiwan[C]// Proceedings of 6th Asian Conference on Intelligent Information and Database Systems. Bangkok, Thailand: Springer, 2014: 444-453.
    [21]
    Abe A. Curating and mining (big) data[C]// Proceedings of IEEE 13th International Conference on Data Mining Workshops. Dallas, USA: IEEE Press, 2013: 664-671.
    [22]
    Wang H, Xu F J, Hu X H, et al. IdeaGraph: A graph-based algorithm of mining latent information for human cognition[C]// Proceedings of 2013 IEEE International Conference on Systems, Man, and Cybernetics. Manchester, UK: IEEE Press, 2013: 952-957.
    [23]
    Shimizu A, Suzuki Y, Ueda H. A dress coordination robot system which can improve user's ability by a dialogue robot[J]. Communications in Computer and Information Science, 2013, 374: 606-610.
    [24]
    Wang H, Ohsawa Y. Idea discovery: A scenario-based systematic approach for decision making in market innovation[J]. Expert Systems with Applications, 2013, 40(2): 429-438.
    [25]
    Zhang C, Wang H, Xu F J, et al. IdeaGraph plus: A topic-based algorithm for perceiving unnoticed events[C]// Proceedings of IEEE 13th International Conference on Data Mining Workshops. Dallas, USA: IEEE Press, 2013: 735-741.
    [26]
    Su I. Chance discovery in teaching of EFL writing using weak tie to innovation model (WTTI Model)[C]// Proceedings of 3rd International Conference on Innovations in Bio-Inspired Computing and Applications. Taiwan, China: IEEE Press, 2012: 344-349.
    [27]
    Abe A. Visualization as curation with a holistic communication[C]// Proceedings of 2012 Conference on Technologies and Applications of Artificial Intelligence. Washington, USA: IEEE Press, 2012: 266-271.
    [28]
    Wang H, Ohsawa Y, Nishihara Y. Innovation support system for creative product design based on chance discovery[j]. Expert Systems with Applications, 2012, 39(5): 4890-4897.
    [29]
    Ohsawa Y, Yada K. Discovery of significant events for decision making[J]. Information Sciences, 2009, 79(11): 1567-1569.
    [30]
    Wang H, Ohsawa Y, Lv P, et al. IdeaGraph: Turning data into human insights for collective intelligence[J]. Advances in Intelligent Systems and Computing, 2014, 213: 33-44.
    [31]
    Khezerlou A V, Alizadeh S. A new model for discovering process trees from event logs[J]. Applied Intelligence, 2014, 41( 3):7 25-735.
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    [1]
    Ohsawa Y. Chance Discovery[M]. Springer- Verlag, 2003.
    [2]
    Abe A. Cognitive chance discovery: From abduction to affordance and curation[J] International Journal of Cognitive Informatics and Cognitive Computing, 2013, 8(2): 308-314.
    [3]
    McBurney P, Parsons S. Chance discovery and scenario analysis[J]. New Generation Computing, 2003, 21(1): 13-22.
    [4]
    张振亚, 程红梅, 王煦法. 从数据挖掘到机会/征兆发现[J]. 计算机科学, 2007, 34(10): 188-191.
    [5]
    张振亚, 程红梅, 张曙光. 基于六度分离理论的机会发现场景构造方法[J]. 模式识别与人工智能, 2011, 24(3): 332-339.
    Zhang Z Y, Cheng H M, Zhang S G. Anapproach to construction of scenario map in chance discovery based on six degree of separation theory[J]. Pattern Recognition and Artificial Intelligence, 2011, 24(3): 332-339.
    [6]
    张振亚, 程红梅, 张曙光. 机会发现中简单场景构造方法研究[J]. 计算机工程, 2011, 37(8): 192-193, 196.
    Zhang Z Y, Cheng H M, Zhang S G.Research on approach of simple scenario map construction in chance discovery[J]. Computer Engineering, 2011, 37(8): 192-193, 196.
    [7]
    Rybakov V V. Chance discovery and unification in linear modal logic[C]// Proceeding of 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Kaiserslautern, Germany: Springer, 2011: 478-485.
    [8]
    Chiu T F. An integration of grounded theory and chance discovery to explore the technology opportunity[J]. International Journal of Intelligent Information and Database Systems, 2012, 6(3): 231-254.
    [9]
    Abe A. Relation between chance discovery and Black Swan awareness[C]// Proceeding of 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Kaiserslautern, Germany: Springer, 2011: 495-504.
    [10]
    Ohsawa Y, Matsumura N, Okazaki N. Understanding scenarios of individual patients of hepatitis in double helical process involving KeyGraph and DSV[C]// Proceeding of 4th IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology. Springer, 2005:456-469.
    [11]
    Ohsawa Y, Nara Y. Understanding Internet users on double helical model of chance-discovery process[C]// Proceedings of the IEEE International Symposium on Intelligent Control. Baltimore, USA: IEEE Press, 2002: 844-849.
    [12]
    Oehlmann R, Gill B. A diagrammatic approach to discovering chances in team relationships[C]// Proceedings of 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Kaiserslautern, Germany: Springer, 2011:440-441
    [13]
    何先友，杨惠，李惠娟，等. 空间情境模型的更新：认知方式的影响[J]. 心理学报，2011，43(11): 1247-1262.
    [14]
    李金波，许百华，田学红.人机交互中认知负荷变化预测模型的构建[J]. 心理学报，2010，42(5): 559-568.
    [15]
    王沛，林崇德. 社会认知的理论模型综述[J].心理科学，2002，25(1): 73-75.
    [16]
    Gasson S, Waters J. Using a grounded theory approach to study online collaboration behaviors[J]. European Journal of Information Systems, 2013, 22(1): 95-118.
    [17]
    Hoda R, Noble J, Marshall S. Developing a grounded theory to explain the practices of self-organizing Agile teams[J]. Empirical Software Engineering, 2012, 17(6): 609-639.
    [18]
    Chien Ming-Kuei, Chang Te-Ming, Kuo Wei-Chun, Applying Grounded Theory to study green supply chain management practices in Taiwan's industry[C]// International Technology Management Conference. Bangalore, India: IEEE Press, 2012: 129-136.
    [19]
    Chiu T F. An integration of grounded theory and chance discovery to explore the technology opportunity[J]. International Journal of Intelligent Information and Database Systems, 2012, 6(3): 231-254.
    [20]
    Yang F S, Wang A L, Yang Y T. Using chance discovery in recruiting strategies to explore potential students in Taiwan[C]// Proceedings of 6th Asian Conference on Intelligent Information and Database Systems. Bangkok, Thailand: Springer, 2014: 444-453.
    [21]
    Abe A. Curating and mining (big) data[C]// Proceedings of IEEE 13th International Conference on Data Mining Workshops. Dallas, USA: IEEE Press, 2013: 664-671.
    [22]
    Wang H, Xu F J, Hu X H, et al. IdeaGraph: A graph-based algorithm of mining latent information for human cognition[C]// Proceedings of 2013 IEEE International Conference on Systems, Man, and Cybernetics. Manchester, UK: IEEE Press, 2013: 952-957.
    [23]
    Shimizu A, Suzuki Y, Ueda H. A dress coordination robot system which can improve user's ability by a dialogue robot[J]. Communications in Computer and Information Science, 2013, 374: 606-610.
    [24]
    Wang H, Ohsawa Y. Idea discovery: A scenario-based systematic approach for decision making in market innovation[J]. Expert Systems with Applications, 2013, 40(2): 429-438.
    [25]
    Zhang C, Wang H, Xu F J, et al. IdeaGraph plus: A topic-based algorithm for perceiving unnoticed events[C]// Proceedings of IEEE 13th International Conference on Data Mining Workshops. Dallas, USA: IEEE Press, 2013: 735-741.
    [26]
    Su I. Chance discovery in teaching of EFL writing using weak tie to innovation model (WTTI Model)[C]// Proceedings of 3rd International Conference on Innovations in Bio-Inspired Computing and Applications. Taiwan, China: IEEE Press, 2012: 344-349.
    [27]
    Abe A. Visualization as curation with a holistic communication[C]// Proceedings of 2012 Conference on Technologies and Applications of Artificial Intelligence. Washington, USA: IEEE Press, 2012: 266-271.
    [28]
    Wang H, Ohsawa Y, Nishihara Y. Innovation support system for creative product design based on chance discovery[j]. Expert Systems with Applications, 2012, 39(5): 4890-4897.
    [29]
    Ohsawa Y, Yada K. Discovery of significant events for decision making[J]. Information Sciences, 2009, 79(11): 1567-1569.
    [30]
    Wang H, Ohsawa Y, Lv P, et al. IdeaGraph: Turning data into human insights for collective intelligence[J]. Advances in Intelligent Systems and Computing, 2014, 213: 33-44.
    [31]
    Khezerlou A V, Alizadeh S. A new model for discovering process trees from event logs[J]. Applied Intelligence, 2014, 41( 3):7 25-735.
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